Labeled multi-bernoulli track-before-detect for multi-target tracking in video
Tharindu Rathnayake, Amirali Khodadadian Gostar, Reza Hoseinnezhad, Alireza Bab‐Hadiashar · RMIT Research Repository (RMIT University Library) · 2015
This paper presents a labeled multi-Bernoulli filter for track-before-detect with a special focus on visual tracking of multiple targets in video. We show that labeled multi-Bernoulli distribution is a conjugate prior for an image likelihood function with a specific separable form. Following a previously formulated likelihood function (with the desirable separable form) using background subtraction, we apply our proposed labeled multi- Bernoulli filter. Our simulation results show that the proposed solution can successfully track multiple targets in a public visual tracking dataset. Comparative results show superior tracking performance compared with recent competing methods.